Discovery of Web frequent patterns and user characteristics from Web access logs: a framework for dynamic Web personalization

Author

Dua, Sumeet ; Cho, Eungchun ; Iyengar, S.S.

Author_Institution

Louisiana State Univ., Baton Rouge, LA, USA

fYear

2000

fDate

2000

Firstpage

3

Lastpage

8

Abstract

An automatic discovery method that discovers frequent access routines for unique clients from Web access log files is presented. The proposed algorithm develops novel techniques to extract the sets of all predictive access sequences from semi-structured Web access logs. Important user access patterns are manifested through the frequent traversal paths, thus helping to understand user surfing behaviors. The predictive access routines discovered by AllFreSeq are also useful for understanding and improving Web site domain tree

Keywords

client-server systems; data mining; information resources; AllFreSeq; Web access log files; Web frequent pattern discovery; Web site domain tree; automatic discovery method; dynamic Web personalization framework; frequent access routines; frequent traversal paths; predictive access routines; predictive access sequences; semi-structured Web access logs; unique clients; user access patterns; user characteristics; user surfing behaviors; Costs; Data mining; Databases; History; Information retrieval; Internet; Performance analysis; System analysis and design; Uniform resource locators; Web server;

fLanguage

English

Publisher

ieee

Conference_Titel

Application-Specific Systems and Software Engineering Technology, 2000. Proceedings. 3rd IEEE Symposium on

Conference_Location

Richardson, TX

Print_ISBN

0-7695-0559-7

Type

conf

DOI

10.1109/ASSET.2000.888025

Filename

888025